Bibliographic record
Abstract
The eastern cougar once ranged from eastern Canada to Georgia, thriving in the mountains and forests of Appalachia and its surroundings. Before Europeans arrived, cougars roamed freely. Soon after the European colonization of the United States, settlers came to see the eastern cougar as a threat. For centuries, cougars were killed mercilessly and recklessly. State governments placed bounties on the cougars, paying citizens for the cats’ torn away scalps. By 1850, eastern cougars were considered rare. By 1900, they were almost entirely extirpated south of the Mississippi. However, although the last known eastern cougar was killed in Maine in 1938, the cougar was not formally declared extinct until 2018. For those 80 years, legends and misperceptions kept the animal alive. Even today, the Fish and Wildlife Service receives hundreds of reported eastern cougar sightings each year. Ninety percent are other animals; the remainder are escaped captives or cougars migrating from the west. This piece, combining narrative, poetic voice, and scientific and anthropological data, will examine the life and death of the eastern cougar, the parts humans have played in its actual extinction and the denial of its extinction, and human impact on biodiversity and extinction today.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".